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Multi-Objective Optimization Model for Partner Selection in a Market-Oriented Dynamic Collaborative Cloud Service Platform
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- Authors
- Mohammad Mehedi Hassan, Biao Song, Seung Min Han, Eui Nam Huh, Chang Woo Yoon, Won Ryu
- Issue Date
- 2009-11
- Citation
- International Conference on Tools with Artificial Intelligence (ICTAI) 2009, pp.637-644
- Language
- English
- Type
- Conference Paper
- Abstract
- In this paper, we propose a promising multi-objective (MO) optimization model for partner selection in a market-oriented dynamic collaboration (DC) platform of Cloud providers (CPs) to minimize the conflicts among providers that may happen when negotiating among providers. The model not only uses their individual information (INI) but also past collaborative relationship information (PRI) for partner selection which is seldom considered in existing approaches. A multi-objective genetic algorithm (MOGA) called MOGA-IC is also proposed to solve the model as the model is NP-hard. The algorithm is developed using two popular MOGAs- NSGAII and SPEA2. The experimental results show that MOGAIC with NSGA-II outperformed the MOGA-IC with SPEA2 in finding useful Pareto optimal solution sets. In addition, other simulation experiments are conducted to verify the effectiveness of the MOGA-IC in terms of satisfactory partner selection and conflicts minimization. © 2009 IEEE.
- KSP Keywords
- Cloud Service Platform, Cloud providers, Existing Approaches, Market-oriented, Multi-objective Genetic Algorithm, Multi-objective optimization(MOP), NP-hard, NSGA-II, Partner selection, Simulation and experiment, collaborative cloud service